Characterizing the N- and C-terminal Small Ubiquitin-like Modifier (SUMO)-interacting Motifs of the Scaffold Protein DAXX
Bibliographic record
Abstract
DAXX is a scaffold protein with diverse roles that often depend upon binding SUMO via its N- and/or C-terminal SUMO-interacting motifs (SIM-N and SIM-C). Using NMR spectroscopy, we characterized the in vitro binding properties of peptide models of SIM-N and SIM-C to SUMO-1 and SUMO-2. In each case, binding was mediated by hydrophobic and electrostatic interactions and weakened with increasing ionic strength. Neither isolated SIM showed any significant paralog specificity, and the measured μM range K(D) values of SIM-N toward both SUMO-1 and SUMO-2 were ∼4-fold lower than those of SIM-C. Furthermore, SIM-N bound SUMO-1 predominantly in a parallel orientation, whereas SIM-C interconverted between parallel and antiparallel binding modes on an ms to μs time scale. The differences in affinities and binding modes are attributed to the differences in charged residues that flank the otherwise identical hydrophobic core sequences of the two SIMs. In addition, within its native context, SIM-N bound intramolecularly to the adjacent N-terminal helical bundle domain of DAXX, thus reducing its apparent affinity for SUMO. This behavior suggests a possible autoregulatory mechanism for DAXX. The interaction of a C-terminal fragment of DAXX with an N-terminal fragment of the sumoylated Ets1 transcription factor was mediated by SIM-C. Importantly, this interaction did not involve any direct contacts between DAXX and Ets1, but rather was derived from the non-covalent binding of SIM-C to SUMO-1, which in turn was covalently linked to the unstructured N-terminal segment of Ets1. These results provide insights into the binding mechanisms and hence biological roles of the DAXX SUMO-interacting motifs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".